Displaying publications 1 - 20 of 42 in total

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  1. Yick YY, Buratto LG, Schaefer A
    Neuroreport, 2016 08 03;27(11):864-8.
    PMID: 27295027 DOI: 10.1097/WNR.0000000000000628
    Here, we report evidence that electrophysiological neural activity preceding the onset of emotional pictures can predict whether they will be remembered or forgotten 24 h later, whereas the same effect was not observed for neutral pictures. In contrast to previous research, we observed this effect using a paradigm in which participants could not predict the emotional or the neutral content of the pictures before their onset. These effects were obtained alongside significant behavioural effects of superior recognition memory for emotional compared with neutral items. These findings suggest that the preferential encoding of emotional events in memory is determined by fluctuations in the availability of processing resources just before event onset. This explanation argues in favour of mediational models of emotional memory, which contend that emotional information is preferentially encoded because it mobilizes a greater amount of processing resources than neutral information.
    Matched MeSH terms: Brain Mapping
  2. Manan HA, Franz EA, Yahya N
    Neuroradiology, 2020 Mar;62(3):353-367.
    PMID: 31802156 DOI: 10.1007/s00234-019-02322-w
    PURPOSE: Functional MRI (fMRI) can be employed to non-invasively localize brain regions involved in functional areas of language in patients with brain tumour, for applications including pre-operative mapping. The present systematic review was conducted to explore prevalence of different language paradigms utilised in conjunction with fMRI approaches for pre-operative mapping, with the aim of assessing their effectiveness and suitability.

    METHODS: A systematic literature search of brain tumours in the context of fMRI methods applied to pre-operative mapping for language functional areas was conducted using PubMed/MEDLINE and Scopus electronic database following PRISMA guidelines. The article search was conducted between the earliest record and March 1, 2019. References and citations were checked in Google Scholar database.

    RESULTS: Twenty-nine independent studies were identified, comprising 1031 adult participants with 976 patients characterised with different types and sizes of brain tumours, and the remaining 55 being healthy controls. These studies evaluated functional language areas in patients with brain tumours prior to surgical interventions using language-based fMRI. Results demonstrated that 86% of the studies used a Word Generation Task (WGT) to evoke functional language areas during pre-operative mapping. Fifty-seven percent of the studies that used language-based paradigms in conjunction with fMRI as a pre-operative mapping tool were in agreement with intra-operative results of language localization.

    CONCLUSIONS: WGT was most commonly utilised and is proposed as a suitable and useful technique for a language-based paradigm fMRI for pre-operative mapping. However, based on available evidence, WGT alone is not sufficient. We propose a combination and convergence paradigms for a more sensitive and specific map of language function for pre-operative mapping. A standard guideline for clinical applications should be established.

    Matched MeSH terms: Brain Mapping/methods*
  3. Sabel BA, Hamid AIA, Borrmann C, Speck O, Antal A
    Int J Psychophysiol, 2020 08;154:80-92.
    PMID: 30978369 DOI: 10.1016/j.ijpsycho.2019.04.002
    BACKGROUND: Modifying brain activity using non-invasive, low intensity transcranial electrical brain stimulation (TES) has rapidly increased during the past 20 years. Alternating current stimulation (ACS), for example, has been shown to alter brain rhythm activities and modify neuronal functioning in the visual system. Daily application of transorbital ACS to patients with optic nerve damage induces functional connectivity reorganization, and partially restores vision. While ACS is thought to mainly modify neuronal mechanisms, e.g. changes in brain oscillations that can be detected by EEG, it is still an open question, whether and how it may alter BOLD activity.

    OBJECTIVE: We evaluated whether transorbital ACS modulates BOLD activity in early visual cortex using high-resolution 7 Tesla functional magnetic resonance imaging (fMRI).

    METHODS: In this feasibility study transorbital ACS in the alpha range and sham ACS was applied in a random block design in five healthy subjects for 20 min at 1 mA. Brain activation in the visual areas V1, V2 and V3 were measured using 7 Tesla fMRI-based retinotopic mapping at the time points before (baseline) and after stimulation. In addition, we collected data from one hemianopic stroke patient with visual cortex damage after ten daily sessions with 25-50 min stimulation duration.

    RESULTS: In healthy subjects transorbital ACS increased the activated cortical surface area, decreased the fMRI response amplitude and increased coherence in the visual cortex, which was most prominent in the full field task. In the patient, stimulation improved contrast sensitivity in the central visual field. BOLD amplitudes and coherence values were increased in most early visual areas in both hemispheres, with the most pronounced activation detected during eccentricity testing in retinotopic mapping.

    CONCLUSIONS: This feasibility study showed that transorbital ACS modifies BOLD activity to visual stimulation, which outlasts the duration of the AC stimulation. This is in line with earlier neurophysiological findings of increased power in EEG recordings and functional connectivity reorganization in patients with impaired vision. Accordingly, the larger BOLD response area after stimulation can be explained by more coherent activation and lower variability in the activation. Alternatively, increased neuronal activity can also be taken into account. Controlled trials are needed to systematically evaluate the potential of repetitive transorbital ACS to improve visual function after visual pathway stroke and to determine the cause-effect relationship between neural and BOLD activity changes.

    Matched MeSH terms: Brain Mapping
  4. Nisar H, Malik AS, Ullah R, Shim SO, Bawakid A, Khan MB, et al.
    Adv Exp Med Biol, 2015;823:159-74.
    PMID: 25381107 DOI: 10.1007/978-3-319-10984-8_9
    The fundamental step in brain research deals with recording electroencephalogram (EEG) signals and then investigating the recorded signals quantitatively. Topographic EEG (visual spatial representation of EEG signal) is commonly referred to as brain topomaps or brain EEG maps. In this chapter, full search full search block motion estimation algorithm has been employed to track the brain activity in brain topomaps to understand the mechanism of brain wiring. The behavior of EEG topomaps is examined throughout a particular brain activation with respect to time. Motion vectors are used to track the brain activation over the scalp during the activation period. Using motion estimation it is possible to track the path from the starting point of activation to the final point of activation. Thus it is possible to track the path of a signal across various lobes.
    Matched MeSH terms: Brain Mapping
  5. Manan HA, Franz EA, Yahya N
    Eur J Cancer Care (Engl), 2021 Jul;30(4):e13428.
    PMID: 33592671 DOI: 10.1111/ecc.13428
    PURPOSE: Resting-state functional Magnetic Resonance Imaging (rs-fMRI) is suggested to be a viable option for pre-operative mapping for patients with brain tumours. However, it remains an open issue whether the tool is useful in the clinical setting compared to task-based fMRI (T-fMRI) and intraoperative mapping. Thus, a systematic review was conducted to investigate the usefulness of this technique.

    METHODS: A systematic literature search of rs-fMRI methods applied as a pre-operative mapping tool was conducted using the PubMed/MEDLINE and Cochrane Library electronic databases following PRISMA guidelines.

    RESULTS: Results demonstrated that 50% (six out of twelve) of the studies comparing rs-fMRI and T-fMRI showed good concordance for both language and sensorimotor networks. In comparison to intraoperative mapping, 86% (six out of seven) studies found a good agreement to rs-fMRI. Finally, 87% (twenty out of twenty-three) studies agreed that rs-fMRI is a suitable and useful pre-operative mapping tool.

    CONCLUSIONS: rs-fMRI is a promising technique for pre-operative mapping in assessing the functional brain areas. However, the agreement between rs-fMRI with other techniques, including T-fMRI and intraoperative maps, is not yet optimal. Studies to ascertain and improve the sophistication in pre-processing of rs-fMRI imaging data are needed.

    Matched MeSH terms: Brain Mapping
  6. Huang SG, Samdin SB, Ting CM, Ombao H, Chung MK
    J Neurosci Methods, 2020 02 01;331:108480.
    PMID: 31760059 DOI: 10.1016/j.jneumeth.2019.108480
    BACKGROUND: Recent studies have indicated that functional connectivity is dynamic even during rest. A common approach to modeling the dynamic functional connectivity in whole-brain resting-state fMRI is to compute the correlation between anatomical regions via sliding time windows. However, the direct use of the sample correlation matrices is not reliable due to the image acquisition and processing noises in resting-sate fMRI.

    NEW METHOD: To overcome these limitations, we propose a new statistical model that smooths out the noise by exploiting the geometric structure of correlation matrices. The dynamic correlation matrix is modeled as a linear combination of symmetric positive-definite matrices combined with cosine series representation. The resulting smoothed dynamic correlation matrices are clustered into disjoint brain connectivity states using the k-means clustering algorithm.

    RESULTS: The proposed model preserves the geometric structure of underlying physiological dynamic correlation, eliminates unwanted noise in connectivity and obtains more accurate state spaces. The difference in the estimated dynamic connectivity states between males and females is identified.

    COMPARISON WITH EXISTING METHODS: We demonstrate that the proposed statistical model has less rapid state changes caused by noise and improves the accuracy in identifying and discriminating different states.

    CONCLUSIONS: We propose a new regression model on dynamically changing correlation matrices that provides better performance over existing windowed correlation and is more reliable for the modeling of dynamic connectivity.

    Matched MeSH terms: Brain Mapping
  7. Sanchez Bornot JM, Wong-Lin K, Ahmad AL, Prasad G
    Brain Topogr, 2018 11;31(6):895-916.
    PMID: 29546509 DOI: 10.1007/s10548-018-0640-0
    The brain's functional connectivity (FC) estimated at sensor level from electromagnetic (EEG/MEG) signals can provide quick and useful information towards understanding cognition and brain disorders. Volume conduction (VC) is a fundamental issue in FC analysis due to the effects of instantaneous correlations. FC methods based on the imaginary part of the coherence (iCOH) of any two signals are readily robust to VC effects, but neglecting the real part of the coherence leads to negligible FC when the processes are truly connected but with zero or π-phase (modulus 2π) interaction. We ameliorate this issue by proposing a novel method that implements an envelope of the imaginary coherence (EIC) to approximate the coherence estimate of supposedly active underlying sources. We compare EIC with state-of-the-art FC measures that included lagged coherence, iCOH, phase lag index (PLI) and weighted PLI (wPLI), using bivariate autoregressive and stochastic neural mass models. Additionally, we create realistic simulations where three and five regions were mapped on a template cortical surface and synthetic MEG signals were obtained after computing the electromagnetic leadfield. With this simulation and comparison study, we also demonstrate the feasibility of sensor FC analysis using receiver operating curve analysis whilst varying the signal's noise level. However, these results should be interpreted with caution given the known limitations of the sensor-based FC approach. Overall, we found that EIC and iCOH demonstrate superior results with most accurate FC maps. As they complement each other in different scenarios, that will be important to study normal and diseased brain activity.
    Matched MeSH terms: Brain Mapping/methods
  8. Babu MGR, Kadavigere R, Koteshwara P, Sathian B, Rai KS
    Sci Rep, 2020 09 30;10(1):16177.
    PMID: 32999361 DOI: 10.1038/s41598-020-73221-x
    Studies provide evidence that practicing meditation enhances neural plasticity in reward processing areas of brain. No studies till date, provide evidence of such changes in Rajyoga meditation (RM) practitioners. The present study aimed to identify grey matter volume (GMV) changes in reward processing areas of brain and its association with happiness scores in RM practitioners compared to non-meditators. Structural MRI of selected participants matched for age, gender and handedness (n = 40/group) were analyzed using voxel-based morphometric method and Oxford Happiness Questionnaire (OHQ) scores were correlated. Significant increase in OHQ happiness scores were observed in RM practitioners compared to non-meditators. Whereas, a trend towards significance was observed in more experienced RM practitioners, on correlating OHQ scores with hours of meditation experience. Additionally, in RM practitioners, higher GMV were observed in reward processing centers-right superior frontal gyrus, left inferior orbitofrontal cortex (OFC) and bilateral precuneus. Multiple regression analysis showed significant association between OHQ scores of RM practitioners and reward processing regions right superior frontal gyrus, left middle OFC, right insula and left anterior cingulate cortex. Further, with increasing hours of RM practice, a significant positive association was observed in bilateral ventral pallidum. These findings indicate that RM practice enhances GMV in reward processing regions associated with happiness.
    Matched MeSH terms: Brain Mapping
  9. Abdullah JM
    Malays J Med Sci, 2021 Apr;28(2):1-14.
    PMID: 33958956 DOI: 10.21315/mjms2021.28.2.1
    Last year, there was an increase in the amount of manpower in Malaysia, especially in terms of the numbers of neurosurgeons, cognitive neuroscientists and clinical psychologists. One way to increase the number of cognitive neurotechnologists in the country in 2021 is to allow neuroscientists to register as neurotechnologists with the Malaysian Board of Technologists (MBOT). The Malaysian Brain Mapping project has risen from its humble beginnings as an initiative of the Universiti Sains Malaysia Brain Mapping Group in 2017. There is currently a proposal for its entry into the national arena via the Precision Medicine Initiative with the Academy Science Malaysia, the Ministry of Science, Technology and Innovation, Ministry of Higher Education and Ministry of Health. The current Malaysian Government's Science, Technology, Innovation and Economy (STIE) plan was launched in 2020, leading to the establishment of neurotechnology as one of 10 STIE drivers.
    Matched MeSH terms: Brain Mapping
  10. Ramli N, Rahmat K, Lim KS, Tan CT
    Eur J Radiol, 2015 Sep;84(9):1791-800.
    PMID: 26187861 DOI: 10.1016/j.ejrad.2015.03.024
    Identification of the epileptogenic zone is of paramount importance in refractory epilepsy as the success of surgical treatment depends on complete resection of the epileptogenic zone. Imaging plays an important role in the locating and defining anatomic epileptogenic abnormalities in patients with medically refractory epilepsy. The aim of this article is to present an overview of the current MRI sequences used in epilepsy imaging with special emphasis of lesion seen in our practices. Optimisation of epilepsy imaging protocols are addressed and current trends in functional MRI sequences including MR spectroscopy, diffusion tensor imaging and fusion MR with PET and SPECT are discussed.
    Matched MeSH terms: Brain Mapping/methods*
  11. Chua CS, Bai CH, Shiao CY, Hsu CY, Cheng CW, Yang KC, et al.
    PLoS One, 2017;12(8):e0183960.
    PMID: 28859146 DOI: 10.1371/journal.pone.0183960
    BACKGROUND & AIMS: Irritable bowel syndrome (IBS) manifests as chronic abdominal pain. One pathophysiological theory states that the brain-gut axis is responsible for pain control in the intestine. Although several studies have discussed the structural changes in the brain of IBS patients, most of these studies have been conducted in Western populations. Different cultures and sexes experience different pain sensations and have different pain responses. Accordingly, we aimed to identify the specific changes in the cortical thickness of Asian women with IBS and to compare these data to those of non-Asian women with IBS.

    METHODS: Thirty Asian female IBS patients (IBS group) and 39 healthy individuals (control group) were included in this study. Brain structural magnetic resonance imaging was performed. We used FreeSurfer to analyze the differences in the cortical thickness and their correlations with patient characteristics.

    RESULTS: The left cuneus, left rostral middle frontal cortex, left supramarginal cortex, right caudal anterior cingulate cortex, and bilateral insula exhibited cortical thinning in the IBS group compared with those in the controls. Furthermore, the brain cortical thickness correlated negatively the severity as well as duration of abdominal pain.

    CONCLUSIONS: Some of our findings differ from those of Western studies. In our study, all of the significant brain regions in the IBS group exhibited cortical thinning compared with those in the controls. The differences in cortical thickness between the IBS patients and controls may provide useful information to facilitate regulating abdominal pain in IBS patients. These findings offer insights into the association of different cultures and sexes with differences in cortical thinning in patients with IBS.

    Matched MeSH terms: Brain Mapping
  12. Poznanski RR
    J Integr Neurosci, 2009 Sep;8(3):345-69.
    PMID: 19938210
    The continuity of the mind is suggested to mean the continuous spatiotemporal dynamics arising from the electrochemical signature of the neocortex: (i) globally through volume transmission in the gray matter as fields of neural activity, and (ii) locally through extrasynaptic signaling between fine distal dendrites of cortical neurons. If the continuity of dynamical systems across spatiotemporal scales defines a stream of consciousness then intentional metarepresentations as templates of dynamic continuity allow qualia to be semantically mapped during neuroimaging of specific cognitive tasks. When interfaced with a computer, such model-based neuroimaging requiring new mathematics of the brain will begin to decipher higher cognitive operations not possible with existing brain-machine interfaces.
    Matched MeSH terms: Brain Mapping/methods*
  13. Elaina NS, Malik AS, Shams WK, Badruddin N, Abdullah JM, Reza MF
    Clin Neuroradiol, 2018 Jun;28(2):267-281.
    PMID: 28116447 DOI: 10.1007/s00062-017-0557-0
    PURPOSE: To localize sensorimotor cortical activation in 10 patients with frontoparietal tumors using quantitative magnetoencephalography (MEG) with noise-normalized approaches.

    MATERIAL AND METHODS: Somatosensory evoked magnetic fields (SEFs) were elicited in 10 patients with somatosensory tumors and in 10 control participants using electrical stimulation of the median nerve via the right and left wrists. We localized the N20m component of the SEFs using dynamic statistical parametric mapping (dSPM) and standardized low-resolution brain electromagnetic tomography (sLORETA) combined with 3D magnetic resonance imaging (MRI). The obtained coordinates were compared between groups. Finally, we statistically evaluated the N20m parameters across hemispheres using non-parametric statistical tests.

    RESULTS: The N20m sources were accurately localized to Brodmann area 3b in all members of the control group and in seven of the patients; however, the sources were shifted in three patients relative to locations outside the primary somatosensory cortex (SI). Compared with the affected (tumor) hemispheres in the patient group, N20m amplitudes and the strengths of the current sources were significantly lower in the unaffected hemispheres and in both hemispheres of the control group. These results were consistent for both dSPM and sLORETA approaches.

    CONCLUSION: Tumors in the sensorimotor cortex lead to cortical functional reorganization and an increase in N20m amplitude and current-source strengths. Noise-normalized approaches for MEG analysis that are integrated with MRI show accurate and reliable localization of sensorimotor function.

    Matched MeSH terms: Brain Mapping
  14. Ting CM, Seghouane AK, Khalid MU, Salleh ShH
    Neural Comput, 2015 Sep;27(9):1857-71.
    PMID: 26161816 DOI: 10.1162/NECO_a_00765
    We consider the problem of selecting the optimal orders of vector autoregressive (VAR) models for fMRI data. Many previous studies used model order of one and ignored that it may vary considerably across data sets depending on different data dimensions, subjects, tasks, and experimental designs. In addition, the classical information criteria (IC) used (e.g., the Akaike IC (AIC)) are biased and inappropriate for the high-dimensional fMRI data typically with a small sample size. We examine the mixed results on the optimal VAR orders for fMRI, especially the validity of the order-one hypothesis, by a comprehensive evaluation using different model selection criteria over three typical data types--a resting state, an event-related design, and a block design data set--with varying time series dimensions obtained from distinct functional brain networks. We use a more balanced criterion, Kullback's IC (KIC) based on Kullback's symmetric divergence combining two directed divergences. We also consider the bias-corrected versions (AICc and KICc) to improve VAR model selection in small samples. Simulation results show better small-sample selection performance of the proposed criteria over the classical ones. Both bias-corrected ICs provide more accurate and consistent model order choices than their biased counterparts, which suffer from overfitting, with KICc performing the best. Results on real data show that orders greater than one were selected by all criteria across all data sets for the small to moderate dimensions, particularly from small, specific networks such as the resting-state default mode network and the task-related motor networks, whereas low orders close to one but not necessarily one were chosen for the large dimensions of full-brain networks.
    Matched MeSH terms: Brain Mapping*
  15. Begum T, Reza F, Ahmed I, Abdullah JM
    J Integr Neurosci, 2014 Mar;13(1):71-88.
    PMID: 24738540 DOI: 10.1142/S0219635214500058
    Simple geometric and organic shapes and their arrangement are being used in different neuropsychology tests for the assessment of cognitive function, special memory and also for the therapy purpose in different patient groups. Until now there is no electrophysiological evidence of cognitive function determination for simple geometric, organic shapes and their arrangement. Then the main objective of this study is to know the cortical processing and amplitude, latency of visual induced N170 and P300 event related potential components on different geometric, organic shapes and their arrangement and different educational influence on it, which is worthwhile to know for the early and better treatment for those patient groups. While education influenced on cognitive function by using auditory oddball task, little is known about the influence of education on cognitive function induced by visual attention task in case of the choice of geometric, organic shapes and their arrangements. Using a 128-electrode sensor net, we studied the responses of the choice of the different geometric and organic shapes randomly in experiment 1 and their arrangements in experiment 2 in the high, medium and low education groups. In both experiments, subjects push the button "1" or "2" if like or dislike, respectively. Total 45 healthy subjects (15 in each group) were recruited. ERPs were measured from 11 electrode sites and analyzed to see the evoked N170/N240 and P300 ERP components. There were no differences between like and dislike in amplitudes even in latencies in every stimulus in both experiments. We fixed geometric shapes and organic shapes stimuli only, not like and dislike. Upon the stimulus types, N170 ERP component was found instead of N240, in occipito-temporal (T5, T6, O1 and O2) locations where the amplitude is the highest at O2 location and P300 was distributed in the central (Cz and Pz) locations in both experiments in all groups. In experiment 1, significant low amplitude and non-significant larger latency of the N170 component are found out at O1 location for both stimuli in low education group comparing medium education groups, but in experiment 2, there is no significant difference between stimuli among groups in amplitude and latency. In both experiments, P300 component was found in Cz and Pz locations though the amplitudes are higher at Cz than Pz areas. In experiment 1, medium education group evoked significantly (geometric shape stimuli, P = 0.05; organic shape stimuli, P = 0.02) higher amplitude of P300 component comparing low education group at Cz location. Whereas, there is no significant difference of amplitudes among groups across stimuli in Cz and Pz locations in experiment 2. Latencies have no significant differences in both experiments among groups also, but longer latency are found in low education group at Cz location comparing medium education group, though not significant. We conclude that simple geometric shapes, organic shapes and their arrangements evoked visual N170 component at temporo-occipital areas with right lateralization and P300 ERP component at centro-parietal areas. Significant low amplitude of N170 and P300 ERP components and longer latencies during different shape stimuli in low education group prove that, low education significantly influence on visual cognitive functions in low education group.
    Matched MeSH terms: Brain Mapping*
  16. Syed Nasser N, Ibrahim B, Sharifat H, Abdul Rashid A, Suppiah S
    J Clin Neurosci, 2019 Jul;65:87-99.
    PMID: 30955950 DOI: 10.1016/j.jocn.2019.03.054
    Functional magnetic resonance imaging (fMRI) is a non-invasive imaging modality that enables the assessment of neural connectivity and oxygen utility of the brain using blood oxygen level dependent (BOLD) imaging sequence. Electroencephalography (EEG), on the other hands, looks at cortical electrical impulses of the brain thus detecting brainwave patterns during rest and thought processing. The combination of these two modalities is called fMRI with simultaneous EEG (fMRI-EEG), which has emerged as a new tool for experimental neuroscience assessments and has been applied clinically in many settings, most commonly in epilepsy cases. Recent advances in imaging has led to fMRI-EEG being utilized in behavioural studies which can help in giving an objective assessment of ambiguous cases and help in the assessment of response to treatment by providing a non-invasive biomarker of the disease processes. We aim to review the role and interpretation of fMRI-EEG in studies pertaining to psychiatric disorders and behavioral abnormalities.
    Matched MeSH terms: Brain Mapping/methods
  17. Al-Hiyali MI, Yahya N, Faye I, Hussein AF
    Sensors (Basel), 2021 Aug 04;21(16).
    PMID: 34450699 DOI: 10.3390/s21165256
    The functional connectivity (FC) patterns of resting-state functional magnetic resonance imaging (rs-fMRI) play an essential role in the development of autism spectrum disorders (ASD) classification models. There are available methods in literature that have used FC patterns as inputs for binary classification models, but the results barely reach an accuracy of 80%. Additionally, the generalizability across multiple sites of the models has not been investigated. Due to the lack of ASD subtypes identification model, the multi-class classification is proposed in the present study. This study aims to develop automated identification of autism spectrum disorder (ASD) subtypes using convolutional neural networks (CNN) using dynamic FC as its inputs. The rs-fMRI dataset used in this study consists of 144 individuals from 8 independent sites, labeled based on three ASD subtypes, namely autistic disorder (ASD), Asperger's disorder (APD), and pervasive developmental disorder not otherwise specified (PDD-NOS). The blood-oxygen-level-dependent (BOLD) signals from 116 brain nodes of automated anatomical labeling (AAL) atlas are used, where the top-ranked node is determined based on one-way analysis of variance (ANOVA) of the power spectral density (PSD) values. Based on the statistical analysis of the PSD values of 3-level ASD and normal control (NC), putamen_R is obtained as the top-ranked node and used for the wavelet coherence computation. With good resolution in time and frequency domain, scalograms of wavelet coherence between the top-ranked node and the rest of the nodes are used as dynamic FC feature input to the convolutional neural networks (CNN). The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. Results of binary classification (ASD vs. NC) and multi-class classification (ASD vs. APD vs. PDD-NOS vs. NC) yielded, respectively, 89.8% accuracy and 82.1% macro-average accuracy, respectively. Findings from this study have illustrated the good potential of wavelet coherence technique in representing dynamic FC between brain nodes and open possibilities for its application in computer aided diagnosis of other neuropsychiatric disorders, such as depression or schizophrenia.
    Matched MeSH terms: Brain Mapping
  18. Habib MA, Ibrahim F, Mohktar MS, Kamaruzzaman SB, Rahmat K, Lim KS
    World Neurosurg, 2016 Apr;88:576-585.
    PMID: 26548833 DOI: 10.1016/j.wneu.2015.10.096
    BACKGROUND: Electroencephalography source imaging (ESI) is a promising tool for localizing the cortical sources of both ictal and interictal epileptic activities. Many studies have shown the clinical usefulness of interictal ESI, but very few have investigated the utility of ictal ESI. The aim of this article is to examine the clinical usefulness of ictal ESI for epileptic focus localization in patients with refractory focal epilepsy, especially extratemporal lobe epilepsy.

    METHODS: Both ictal and interictal ESI were performed by the use of patient-specific realistic forward models and 3 different linear distributed inverse models. Lateralization as well as concordance between ESI-estimated focuses and single-photon emission computed tomography (SPECT) focuses were assessed.

    RESULTS: All the ESI focuses (both ictal and interictal) were found lateralized to the same hemisphere as ictal SPECT focuses. Lateralization results also were in agreement with the lesion sides as visualized on magnetic resonance imaging. Ictal ESI results, obtained from the best-performing inverse model, were fully concordant with the same cortical lobe as SPECT focuses, whereas the corresponding concordance rate is 87.50% in case of interictal ESI.

    CONCLUSIONS: Our findings show that ictal ESI gives fully lateralized and highly concordant results with ictal SPECT and may provide a cost-effective substitute for ictal SPECT.

    Matched MeSH terms: Brain Mapping/methods*
  19. Auer T, Dewiputri WI, Frahm J, Schweizer R
    Neuroscience, 2018 May 15;378:22-33.
    PMID: 27133575 DOI: 10.1016/j.neuroscience.2016.04.034
    Neurofeedback (NFB) allows subjects to learn self-regulation of neuronal brain activation based on information about the ongoing activation. The implementation of real-time functional magnetic resonance imaging (rt-fMRI) for NFB training now facilitates the investigation into underlying processes. Our study involved 16 control and 16 training right-handed subjects, the latter performing an extensive rt-fMRI NFB training using motor imagery. A previous analysis focused on the targeted primary somato-motor cortex (SMC). The present study extends the analysis to the supplementary motor area (SMA), the next higher brain area within the hierarchy of the motor system. We also examined transfer-related functional connectivity using a whole-volume psycho-physiological interaction (PPI) analysis to reveal brain areas associated with learning. The ROI analysis of the pre- and post-training fMRI data for motor imagery without NFB (transfer) resulted in a significant training-specific increase in the SMA. It could also be shown that the contralateral SMA exhibited a larger increase than the ipsilateral SMA in the training and the transfer runs, and that the right-hand training elicited a larger increase in the transfer runs than the left-hand training. The PPI analysis revealed a training-specific increase in transfer-related functional connectivity between the left SMA and frontal areas as well as the anterior midcingulate cortex (aMCC) for right- and left-hand trainings. Moreover, the transfer success was related with training-specific increase in functional connectivity between the left SMA and the target area SMC. Our study demonstrates that NFB training increases functional connectivity with non-targeted brain areas. These are associated with the training strategy (i.e., SMA) as well as with learning the NFB skill (i.e., aMCC and frontal areas). This detailed description of both the system to be trained and the areas involved in learning can provide valuable information for further optimization of NFB trainings.
    Matched MeSH terms: Brain Mapping
  20. Othman EA, Yusoff AN, Mohamad M, Abdul Manan H, Abd Hamid AI, Giampietro V
    J Magn Reson Imaging, 2020 06;51(6):1821-1828.
    PMID: 31794119 DOI: 10.1002/jmri.27016
    BACKGROUND: The auditory and prefrontal cortex supports auditory working memory processing. Many neuroimaging studies have shown hemispheric lateralization of auditory working memory brain regions in the presence of background noise, but few studies have focused on the lateralization of these regions during stochastic resonance.

    PURPOSE: To investigate the effects of stochastic resonance on lateralization of auditory working memory regions, and also to examine the brain-behavior relationship during stochastic resonance.

    STUDY TYPE: Cross-sectional.

    POPULATION/SUBJECTS: Forty healthy young adults (18-24 years old).

    FIELD STRENGTH/SEQUENCE: 3.0T, T1 , and T2 *-weighted imaging.

    ASSESSMENT: The auditory working memory performance was assessed using a backward recall task. Functional magnetic resonance imaging (fMRI) was used to measure brain activity during task performance. Functional MRI data were analyzed using SPM12 and WFU PickAtlas.

    STATISTICAL TESTS: One-way independent analyses of variance (ANOVA) were conducted on the behavioral and functional data to examine the main effect of noise level on performance (P brain activity (P brain activity between hemispheres (P brain activity and behavioral performance.

    RESULTS: Performance was significantly enhanced during the 50 and 55 dB sound pressure level (SPL) conditions via the stochastic resonance mechanism [F(1,195) = 49.17, P 

    Matched MeSH terms: Brain Mapping*
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